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<div class="title">depthNet.h</div>  </div>
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<a href="depthNet_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/*</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> * copy of this software and associated documentation files (the &quot;Software&quot;),</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> * to deal in the Software without restriction, including without limitation</span></div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment"> * the rights to use, copy, modify, merge, publish, distribute, sublicense,</span></div>
<div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment"> * and/or sell copies of the Software, and to permit persons to whom the</span></div>
<div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment"> * Software is furnished to do so, subject to the following conditions:</span></div>
<div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="comment"> * The above copyright notice and this permission notice shall be included in</span></div>
<div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="comment"> * all copies or substantial portions of the Software.</span></div>
<div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="comment"> * THE SOFTWARE IS PROVIDED &quot;AS IS&quot;, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div>
<div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div>
<div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL</span></div>
<div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="comment"> * THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div>
<div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING</span></div>
<div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;<span class="comment"> * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER</span></div>
<div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="comment"> * DEALINGS IN THE SOFTWARE.</span></div>
<div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160; </div>
<div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="preprocessor">#ifndef __DEPTH_NET_H__</span></div>
<div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<span class="preprocessor">#define __DEPTH_NET_H__</span></div>
<div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160; </div>
<div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="tensorNet_8h.html">tensorNet.h</a>&quot;</span></div>
<div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="cudaColormap_8h.html">jetson-utils/cudaColormap.h</a>&gt;</span></div>
<div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160; </div>
<div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160; </div>
<div class="line"><a name="l00034"></a><span class="lineno"><a class="line" href="group__depthNet.html#gab90d8bf9344740081e4c51c014e73c52">   34</a></span>&#160;<span class="preprocessor">#define DEPTHNET_DEFAULT_INPUT   &quot;input_0&quot;</span></div>
<div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160; </div>
<div class="line"><a name="l00040"></a><span class="lineno"><a class="line" href="group__depthNet.html#gadb112003697f3e8ecf1b40fb1a082ca8">   40</a></span>&#160;<span class="preprocessor">#define DEPTHNET_DEFAULT_OUTPUT  &quot;output_0&quot;</span></div>
<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160; </div>
<div class="line"><a name="l00046"></a><span class="lineno"><a class="line" href="group__depthNet.html#ga911dc4ffefb7f5e9f88bead199492bd8">   46</a></span>&#160;<span class="preprocessor">#define DEPTHNET_MODEL_TYPE &quot;monodepth&quot;</span></div>
<div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160; </div>
<div class="line"><a name="l00052"></a><span class="lineno"><a class="line" href="group__depthNet.html#gaf7fedcbd0339376e367939bbcecdd884">   52</a></span>&#160;<span class="preprocessor">#define DEPTHNET_USAGE_STRING  &quot;depthNet arguments: \n&quot;                                                         \</span></div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;<span class="preprocessor">                  &quot;  --network NETWORK    pre-trained model to load, one of the following:\n&quot;   \</span></div>
<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;<span class="preprocessor">                  &quot;                           * fcn-mobilenet\n&quot;                                        \</span></div>
<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;<span class="preprocessor">                  &quot;                           * fcn-resnet18\n&quot;                                         \</span></div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;<span class="preprocessor">                  &quot;                           * fcn-resnet50\n&quot;                                         \</span></div>
<div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;<span class="preprocessor">                  &quot;  --model MODEL        path to custom model to load (onnx)\n&quot;                        \</span></div>
<div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;<span class="preprocessor">                  &quot;  --input_blob INPUT   name of the input layer (default is &#39;&quot; DEPTHNET_DEFAULT_INPUT &quot;&#39;)\n&quot;  \</span></div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;<span class="preprocessor">                  &quot;  --output_blob OUTPUT name of the output layer (default is &#39;&quot; DEPTHNET_DEFAULT_OUTPUT &quot;&#39;)\n&quot;        \</span></div>
<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;<span class="preprocessor">                  &quot;  --profile            enable layer profiling in TensorRT\n\n&quot;</span></div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160; </div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160; </div>
<div class="line"><a name="l00067"></a><span class="lineno"><a class="line" href="group__depthNet.html">   67</a></span>&#160;<span class="keyword">class </span><a class="code" href="group__depthNet.html#classdepthNet">depthNet</a> : <span class="keyword">public</span> <a class="code" href="group__tensorNet.html#classtensorNet">tensorNet</a></div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;{</div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;<span class="keyword">public</span>:</div>
<div class="line"><a name="l00073"></a><span class="lineno"><a class="line" href="group__depthNet.html#a79173edc788bdf267e4622ad0f52e476">   73</a></span>&#160;        <span class="keyword">enum</span> <a class="code" href="group__depthNet.html#a79173edc788bdf267e4622ad0f52e476">VisualizationFlags</a></div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;        {</div>
<div class="line"><a name="l00075"></a><span class="lineno"><a class="line" href="group__depthNet.html#a79173edc788bdf267e4622ad0f52e476a8e00a42ee2103dc6081b8886553b9c91">   75</a></span>&#160;                <a class="code" href="group__depthNet.html#a79173edc788bdf267e4622ad0f52e476a8e00a42ee2103dc6081b8886553b9c91">VISUALIZE_INPUT</a> = (1 &lt;&lt; 0),  </div>
<div class="line"><a name="l00076"></a><span class="lineno"><a class="line" href="group__depthNet.html#a79173edc788bdf267e4622ad0f52e476a8675b85af577753f73916d1087ff3c4e">   76</a></span>&#160;                <a class="code" href="group__depthNet.html#a79173edc788bdf267e4622ad0f52e476a8675b85af577753f73916d1087ff3c4e">VISUALIZE_DEPTH</a> = (1 &lt;&lt; 1),  </div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;        };</div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;        </div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;        <span class="keyword">static</span> uint32_t <a class="code" href="group__depthNet.html#a5d882ef0255213a1950659b661f99424">VisualizationFlagsFromStr</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* str, uint32_t default_value=<a class="code" href="group__depthNet.html#a79173edc788bdf267e4622ad0f52e476a8e00a42ee2103dc6081b8886553b9c91">VISUALIZE_INPUT</a>|<a class="code" href="group__depthNet.html#a79173edc788bdf267e4622ad0f52e476a8675b85af577753f73916d1087ff3c4e">VISUALIZE_DEPTH</a> );</div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160; </div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;        <span class="keyword">static</span> <a class="code" href="group__depthNet.html#classdepthNet">depthNet</a>* <a class="code" href="group__depthNet.html#ada432dd3799aaaa621330be631330165">Create</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* network=<span class="stringliteral">&quot;fcn-mobilenet&quot;</span>, </div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;                                                uint32_t maxBatchSize=<a class="code" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, </div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;                                                <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="code" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>,</div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;                                                <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="code" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, <span class="keywordtype">bool</span> allowGPUFallback=<span class="keyword">true</span> );</div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;        </div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;        <span class="keyword">static</span> <a class="code" href="group__depthNet.html#classdepthNet">depthNet</a>* <a class="code" href="group__depthNet.html#ada432dd3799aaaa621330be631330165">Create</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* model_path, </div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;                                                <span class="keyword">const</span> <span class="keywordtype">char</span>* input=<a class="code" href="group__depthNet.html#gab90d8bf9344740081e4c51c014e73c52">DEPTHNET_DEFAULT_INPUT</a>, </div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;                                                <span class="keyword">const</span> <span class="keywordtype">char</span>* output=<a class="code" href="group__depthNet.html#gadb112003697f3e8ecf1b40fb1a082ca8">DEPTHNET_DEFAULT_OUTPUT</a>, </div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;                                                uint32_t maxBatchSize=<a class="code" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, </div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;                                                <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="code" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>,</div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;                                                <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="code" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, <span class="keywordtype">bool</span> allowGPUFallback=<span class="keyword">true</span> );</div>
<div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;        </div>
<div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;        <span class="keyword">static</span> <a class="code" href="group__depthNet.html#classdepthNet">depthNet</a>* <a class="code" href="group__depthNet.html#ada432dd3799aaaa621330be631330165">Create</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* model_path, <span class="keyword">const</span> <span class="keywordtype">char</span>* input,</div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;                                                <span class="keyword">const</span> <a class="code" href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">Dims3</a>&amp; inputDims, <span class="keyword">const</span> <span class="keywordtype">char</span>* output,</div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;                                                uint32_t maxBatchSize=<a class="code" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, </div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;                                                <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="code" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>,</div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;                                                <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="code" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, <span class="keywordtype">bool</span> allowGPUFallback=<span class="keyword">true</span> );</div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160; </div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;        <span class="keyword">static</span> <a class="code" href="group__depthNet.html#classdepthNet">depthNet</a>* <a class="code" href="group__depthNet.html#ada432dd3799aaaa621330be631330165">Create</a>( <span class="keywordtype">int</span> argc, <span class="keywordtype">char</span>** argv );</div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160; </div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;        <span class="keyword">static</span> <a class="code" href="group__depthNet.html#classdepthNet">depthNet</a>* <a class="code" href="group__depthNet.html#ada432dd3799aaaa621330be631330165">Create</a>( <span class="keyword">const</span> <a class="code" href="group__commandLine.html#classcommandLine">commandLine</a>&amp; cmdLine );</div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;        </div>
<div class="line"><a name="l00137"></a><span class="lineno"><a class="line" href="group__depthNet.html#ade3376a680252cf2aa68f0f1945a6b71">  137</a></span>&#160;        <span class="keyword">static</span> <span class="keyword">inline</span> <span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="group__depthNet.html#ade3376a680252cf2aa68f0f1945a6b71">Usage</a>()               { <span class="keywordflow">return</span> <a class="code" href="group__depthNet.html#gaf7fedcbd0339376e367939bbcecdd884">DEPTHNET_USAGE_STRING</a>; }</div>
<div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160; </div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;        <span class="keyword">virtual</span> <a class="code" href="group__depthNet.html#a0a627d1a246d2eaf92e5ee3c33b8e964">~depthNet</a>();</div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;        </div>
<div class="line"><a name="l00148"></a><span class="lineno"><a class="line" href="group__depthNet.html#afca2eec512a7d7945a9e404eb8e40a56">  148</a></span>&#160;        <span class="keyword">template</span>&lt;<span class="keyword">typename</span> T&gt; <span class="keywordtype">bool</span> <a class="code" href="group__depthNet.html#afca2eec512a7d7945a9e404eb8e40a56">Process</a>( T* image, uint32_t width, uint32_t height )  { <span class="keywordflow">return</span> <a class="code" href="group__depthNet.html#afca2eec512a7d7945a9e404eb8e40a56">Process</a>((<span class="keywordtype">void</span>*)image, width, height, imageFormatFromType&lt;T&gt;()); }</div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;        </div>
<div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__depthNet.html#afca2eec512a7d7945a9e404eb8e40a56">Process</a>( <span class="keywordtype">void</span>* input, uint32_t width, uint32_t height, <a class="code" href="group__imageFormat.html#ga931c48e08f361637d093355d64583406">imageFormat</a> format );</div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160; </div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;        <span class="keyword">template</span>&lt;<span class="keyword">typename</span> T1, <span class="keyword">typename</span> T2&gt; </div>
<div class="line"><a name="l00161"></a><span class="lineno"><a class="line" href="group__depthNet.html#a2e1120d461756c4cab61cde797e43d0f">  161</a></span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__depthNet.html#a2e1120d461756c4cab61cde797e43d0f">Process</a>( T1* input, T2* output, uint32_t width, uint32_t height,</div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;                            <a class="code" href="group__colormap.html#gab66101108d92e39f9ab9283c31da3550">cudaColormapType</a> colormap=<a class="code" href="group__colormap.html#ggab66101108d92e39f9ab9283c31da3550a0d0fcdcd836507523dea555ce4a89632">COLORMAP_VIRIDIS_INVERTED</a>,</div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;                            <a class="code" href="group__cudaFilter.html#ga25d4283643163befe99948d24cc53311">cudaFilterMode</a> filter=<a class="code" href="group__cudaFilter.html#gga25d4283643163befe99948d24cc53311ad8e5de74ec16a7e07145b7c18c885094">FILTER_LINEAR</a> )                                               { <span class="keywordflow">return</span> <a class="code" href="group__depthNet.html#afca2eec512a7d7945a9e404eb8e40a56">Process</a>((<span class="keywordtype">void</span>*)input, imageFormatFromType&lt;T1&gt;(), (<span class="keywordtype">void</span>*)output, imageFormatFromType&lt;T2&gt;(), width, height, colormap, filter); }</div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;        </div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__depthNet.html#afca2eec512a7d7945a9e404eb8e40a56">Process</a>( <span class="keywordtype">void</span>* input, <a class="code" href="group__imageFormat.html#ga931c48e08f361637d093355d64583406">imageFormat</a> input_format, </div>
<div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;                            <span class="keywordtype">void</span>* output, <a class="code" href="group__imageFormat.html#ga931c48e08f361637d093355d64583406">imageFormat</a> output_format,</div>
<div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;                            uint32_t width, uint32_t height, </div>
<div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;                            <a class="code" href="group__colormap.html#gab66101108d92e39f9ab9283c31da3550">cudaColormapType</a> colormap=<a class="code" href="group__colormap.html#ggab66101108d92e39f9ab9283c31da3550a0d0fcdcd836507523dea555ce4a89632">COLORMAP_VIRIDIS_INVERTED</a>,</div>
<div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;                            <a class="code" href="group__cudaFilter.html#ga25d4283643163befe99948d24cc53311">cudaFilterMode</a> filter=<a class="code" href="group__cudaFilter.html#gga25d4283643163befe99948d24cc53311ad8e5de74ec16a7e07145b7c18c885094">FILTER_LINEAR</a> );</div>
<div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160; </div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;        <span class="keyword">template</span>&lt;<span class="keyword">typename</span> T1, <span class="keyword">typename</span> T2&gt; </div>
<div class="line"><a name="l00180"></a><span class="lineno"><a class="line" href="group__depthNet.html#aae07945d10ca9881850400600cf10d08">  180</a></span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__depthNet.html#aae07945d10ca9881850400600cf10d08">Process</a>( T1* input, uint32_t input_width, uint32_t input_height,</div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;                            T2* output, uint32_t output_width, uint32_t output_height,</div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;                            <a class="code" href="group__colormap.html#gab66101108d92e39f9ab9283c31da3550">cudaColormapType</a> colormap=<a class="code" href="group__colormap.html#ggab66101108d92e39f9ab9283c31da3550a02b62792467077e77c5d4cdc8e9e1968">COLORMAP_DEFAULT</a>,</div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;                            <a class="code" href="group__cudaFilter.html#ga25d4283643163befe99948d24cc53311">cudaFilterMode</a> filter=<a class="code" href="group__cudaFilter.html#gga25d4283643163befe99948d24cc53311ad8e5de74ec16a7e07145b7c18c885094">FILTER_LINEAR</a> )                                               { <span class="keywordflow">return</span> <a class="code" href="group__depthNet.html#afca2eec512a7d7945a9e404eb8e40a56">Process</a>((<span class="keywordtype">void</span>*)input, input_width, input_height, imageFormatFromType&lt;T1&gt;(), (<span class="keywordtype">void</span>*)output, output_width, output_height, imageFormatFromType&lt;T2&gt;(), colormap, filter); }                </div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;                            </div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__depthNet.html#afca2eec512a7d7945a9e404eb8e40a56">Process</a>( <span class="keywordtype">void</span>* input, uint32_t input_width, uint32_t input_height, <a class="code" href="group__imageFormat.html#ga931c48e08f361637d093355d64583406">imageFormat</a> input_format,</div>
<div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;                            <span class="keywordtype">void</span>* output, uint32_t output_width, uint32_t output_height, <a class="code" href="group__imageFormat.html#ga931c48e08f361637d093355d64583406">imageFormat</a> output_format,</div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;                            <a class="code" href="group__colormap.html#gab66101108d92e39f9ab9283c31da3550">cudaColormapType</a> colormap=<a class="code" href="group__colormap.html#ggab66101108d92e39f9ab9283c31da3550a02b62792467077e77c5d4cdc8e9e1968">COLORMAP_DEFAULT</a>,</div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;                            <a class="code" href="group__cudaFilter.html#ga25d4283643163befe99948d24cc53311">cudaFilterMode</a> filter=<a class="code" href="group__cudaFilter.html#gga25d4283643163befe99948d24cc53311ad8e5de74ec16a7e07145b7c18c885094">FILTER_LINEAR</a> );</div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160; </div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;        <span class="keyword">template</span>&lt;<span class="keyword">typename</span> T&gt; </div>
<div class="line"><a name="l00199"></a><span class="lineno"><a class="line" href="group__depthNet.html#ae7d152624a7678216ac148e6d025e963">  199</a></span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__depthNet.html#ae7d152624a7678216ac148e6d025e963">Visualize</a>( T* output, uint32_t width, uint32_t height,</div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;                                 <a class="code" href="group__colormap.html#gab66101108d92e39f9ab9283c31da3550">cudaColormapType</a> colormap=<a class="code" href="group__colormap.html#ggab66101108d92e39f9ab9283c31da3550a02b62792467077e77c5d4cdc8e9e1968">COLORMAP_DEFAULT</a>, </div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;                                 <a class="code" href="group__cudaFilter.html#ga25d4283643163befe99948d24cc53311">cudaFilterMode</a> filter=<a class="code" href="group__cudaFilter.html#gga25d4283643163befe99948d24cc53311ad8e5de74ec16a7e07145b7c18c885094">FILTER_LINEAR</a> )                                          { <span class="keywordflow">return</span> <a class="code" href="group__depthNet.html#ae7d152624a7678216ac148e6d025e963">Visualize</a>((<span class="keywordtype">void</span>*)output, width, height, imageFormatFromType&lt;T&gt;(), colormap, filter); }</div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;                                 </div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__depthNet.html#ae7d152624a7678216ac148e6d025e963">Visualize</a>( <span class="keywordtype">void</span>* output, uint32_t width, uint32_t height, <a class="code" href="group__imageFormat.html#ga931c48e08f361637d093355d64583406">imageFormat</a> format,</div>
<div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;                                 <a class="code" href="group__colormap.html#gab66101108d92e39f9ab9283c31da3550">cudaColormapType</a> colormap=<a class="code" href="group__colormap.html#ggab66101108d92e39f9ab9283c31da3550a02b62792467077e77c5d4cdc8e9e1968">COLORMAP_DEFAULT</a>, </div>
<div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;                                 <a class="code" href="group__cudaFilter.html#ga25d4283643163befe99948d24cc53311">cudaFilterMode</a> filter=<a class="code" href="group__cudaFilter.html#gga25d4283643163befe99948d24cc53311ad8e5de74ec16a7e07145b7c18c885094">FILTER_LINEAR</a> );</div>
<div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160; </div>
<div class="line"><a name="l00214"></a><span class="lineno"><a class="line" href="group__depthNet.html#a96554b8c9ba3e710de7fe45f9edc8fc7">  214</a></span>&#160;        <span class="keyword">inline</span> <span class="keywordtype">float</span>* <a class="code" href="group__depthNet.html#a96554b8c9ba3e710de7fe45f9edc8fc7">GetDepthField</a>()<span class="keyword"> const                                             </span>{ <span class="keywordflow">return</span> <a class="code" href="group__tensorNet.html#afcdbdb26dc6e5117f867c83e635a0250">mOutputs</a>[0].CUDA; }</div>
<div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160; </div>
<div class="line"><a name="l00219"></a><span class="lineno"><a class="line" href="group__depthNet.html#a67957d14b680b3d2ef001a55727e3f1d">  219</a></span>&#160;        <span class="keyword">inline</span> uint32_t <a class="code" href="group__depthNet.html#a67957d14b680b3d2ef001a55727e3f1d">GetDepthFieldWidth</a>()<span class="keyword"> const                                      </span>{ <span class="keywordflow">return</span> <a class="code" href="tensorNet_8h.html#a7d959cb65990da8bfea3d941d6daf416">DIMS_W</a>(<a class="code" href="group__tensorNet.html#afcdbdb26dc6e5117f867c83e635a0250">mOutputs</a>[0].dims); }</div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160; </div>
<div class="line"><a name="l00224"></a><span class="lineno"><a class="line" href="group__depthNet.html#a5080fdfd97015e8e77aba3e33275ac37">  224</a></span>&#160;        <span class="keyword">inline</span> uint32_t <a class="code" href="group__depthNet.html#a5080fdfd97015e8e77aba3e33275ac37">GetDepthFieldHeight</a>()<span class="keyword"> const                                     </span>{ <span class="keywordflow">return</span> <a class="code" href="tensorNet_8h.html#a1fc0b1785ea99bd75ec83b1eeb4e6120">DIMS_H</a>(<a class="code" href="group__tensorNet.html#afcdbdb26dc6e5117f867c83e635a0250">mOutputs</a>[0].dims); }</div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160; </div>
<div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__depthNet.html#a9a9695fc22a0468a1688cfeaf806ce8b">SavePointCloud</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* filename );</div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160; </div>
<div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__depthNet.html#a9a9695fc22a0468a1688cfeaf806ce8b">SavePointCloud</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* filename, <span class="keywordtype">float</span>* rgba, uint32_t width, uint32_t height );</div>
<div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160; </div>
<div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__depthNet.html#a9a9695fc22a0468a1688cfeaf806ce8b">SavePointCloud</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* filename, <span class="keywordtype">float</span>* rgba, uint32_t width, uint32_t height,</div>
<div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;                                         <span class="keyword">const</span> float2&amp; focalLength, <span class="keyword">const</span> float2&amp; principalPoint );</div>
<div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160; </div>
<div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__depthNet.html#a9a9695fc22a0468a1688cfeaf806ce8b">SavePointCloud</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* filename, <span class="keywordtype">float</span>* rgba, uint32_t width, uint32_t height,</div>
<div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;                                         <span class="keyword">const</span> <span class="keywordtype">float</span> intrinsicCalibration[3][3] );</div>
<div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160; </div>
<div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__depthNet.html#a9a9695fc22a0468a1688cfeaf806ce8b">SavePointCloud</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* filename, <span class="keywordtype">float</span>* rgba, uint32_t width, uint32_t height,</div>
<div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;                                         <span class="keyword">const</span> <span class="keywordtype">char</span>* intrinsicCalibrationPath );</div>
<div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;                                         </div>
<div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;<span class="keyword">protected</span>:</div>
<div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;        <a class="code" href="group__depthNet.html#a7b7805b7e1875bd7138e19a9949f1318">depthNet</a>();</div>
<div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;        </div>
<div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__depthNet.html#a145bebabbf410e9e74e0d8a040015b1d">allocHistogramBuffers</a>();</div>
<div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__depthNet.html#add24f089796c78eabfdf5edaeb001374">histogramEqualization</a>();</div>
<div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__depthNet.html#a8fb7e1b625a0b9f6d4e046863aceb6ec">histogramEqualizationCUDA</a>();</div>
<div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;        </div>
<div class="line"><a name="l00266"></a><span class="lineno"><a class="line" href="group__depthNet.html#a25ba6711b1c348cf92f0e8c06b703719">  266</a></span>&#160;        int2*     <a class="code" href="group__depthNet.html#a25ba6711b1c348cf92f0e8c06b703719">mDepthRange</a>;</div>
<div class="line"><a name="l00267"></a><span class="lineno"><a class="line" href="group__depthNet.html#a927a4ae2ab52da379e1c5576f3d3fc37">  267</a></span>&#160;        <span class="keywordtype">float</span>*    <a class="code" href="group__depthNet.html#a927a4ae2ab52da379e1c5576f3d3fc37">mDepthEqualized</a>;</div>
<div class="line"><a name="l00268"></a><span class="lineno"><a class="line" href="group__depthNet.html#a397efef0c43950e8aa2048bf4cf1b1b8">  268</a></span>&#160;        uint32_t* <a class="code" href="group__depthNet.html#a397efef0c43950e8aa2048bf4cf1b1b8">mHistogram</a>;</div>
<div class="line"><a name="l00269"></a><span class="lineno"><a class="line" href="group__depthNet.html#a8f9f8636a7bf4c3bbf6da267b550a136">  269</a></span>&#160;        <span class="keywordtype">float</span>*    <a class="code" href="group__depthNet.html#a8f9f8636a7bf4c3bbf6da267b550a136">mHistogramPDF</a>;</div>
<div class="line"><a name="l00270"></a><span class="lineno"><a class="line" href="group__depthNet.html#a1928879f3bb2f489d93c0d122ce2dc4b">  270</a></span>&#160;        <span class="keywordtype">float</span>*    <a class="code" href="group__depthNet.html#a1928879f3bb2f489d93c0d122ce2dc4b">mHistogramCDF</a>;</div>
<div class="line"><a name="l00271"></a><span class="lineno"><a class="line" href="group__depthNet.html#a91a76621c0a3ce9d0b12acc52e6061a9">  271</a></span>&#160;        uint32_t* <a class="code" href="group__depthNet.html#a91a76621c0a3ce9d0b12acc52e6061a9">mHistogramEDU</a>;</div>
<div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;        </div>
<div class="line"><a name="l00274"></a><span class="lineno"><a class="line" href="depthNet_8h.html#a123f753a6274dc3fa4780b176e168a35">  274</a></span>&#160;<span class="preprocessor">        #define DEPTH_FLOAT_TO_INT 1000000</span></div>
<div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;        </div>
<div class="line"><a name="l00277"></a><span class="lineno"><a class="line" href="depthNet_8h.html#a1af887f6a955f2938f1770aa7124aa7b">  277</a></span>&#160;<span class="preprocessor">        #define DEPTH_HISTOGRAM_BINS 256</span></div>
<div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;};</div>
<div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160; </div>
<div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160; </div>
<div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160; </div>
<div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160; </div>
</div><!-- fragment --></div><!-- contents -->
</div><!-- doc-content -->
<div class="ttc" id="agroup__depthNet_html_gadb112003697f3e8ecf1b40fb1a082ca8"><div class="ttname"><a href="group__depthNet.html#gadb112003697f3e8ecf1b40fb1a082ca8">DEPTHNET_DEFAULT_OUTPUT</a></div><div class="ttdeci">#define DEPTHNET_DEFAULT_OUTPUT</div><div class="ttdoc">Name of default output blob for depthNet model.</div><div class="ttdef"><b>Definition:</b> depthNet.h:40</div></div>
<div class="ttc" id="agroup__depthNet_html_a0a627d1a246d2eaf92e5ee3c33b8e964"><div class="ttname"><a href="group__depthNet.html#a0a627d1a246d2eaf92e5ee3c33b8e964">depthNet::~depthNet</a></div><div class="ttdeci">virtual ~depthNet()</div><div class="ttdoc">Destroy.</div></div>
<div class="ttc" id="agroup__depthNet_html_add24f089796c78eabfdf5edaeb001374"><div class="ttname"><a href="group__depthNet.html#add24f089796c78eabfdf5edaeb001374">depthNet::histogramEqualization</a></div><div class="ttdeci">bool histogramEqualization()</div></div>
<div class="ttc" id="agroup__depthNet_html_a2e1120d461756c4cab61cde797e43d0f"><div class="ttname"><a href="group__depthNet.html#a2e1120d461756c4cab61cde797e43d0f">depthNet::Process</a></div><div class="ttdeci">bool Process(T1 *input, T2 *output, uint32_t width, uint32_t height, cudaColormapType colormap=COLORMAP_VIRIDIS_INVERTED, cudaFilterMode filter=FILTER_LINEAR)</div><div class="ttdoc">Process an RGB/RGBA image and map the depth image with the specified colormap.</div><div class="ttdef"><b>Definition:</b> depthNet.h:161</div></div>
<div class="ttc" id="agroup__depthNet_html_gaf7fedcbd0339376e367939bbcecdd884"><div class="ttname"><a href="group__depthNet.html#gaf7fedcbd0339376e367939bbcecdd884">DEPTHNET_USAGE_STRING</a></div><div class="ttdeci">#define DEPTHNET_USAGE_STRING</div><div class="ttdoc">Command-line options able to be passed to depthNet::Create()</div><div class="ttdef"><b>Definition:</b> depthNet.h:52</div></div>
<div class="ttc" id="agroup__depthNet_html_a927a4ae2ab52da379e1c5576f3d3fc37"><div class="ttname"><a href="group__depthNet.html#a927a4ae2ab52da379e1c5576f3d3fc37">depthNet::mDepthEqualized</a></div><div class="ttdeci">float * mDepthEqualized</div><div class="ttdef"><b>Definition:</b> depthNet.h:267</div></div>
<div class="ttc" id="agroup__cudaFilter_html_gga25d4283643163befe99948d24cc53311ad8e5de74ec16a7e07145b7c18c885094"><div class="ttname"><a href="group__cudaFilter.html#gga25d4283643163befe99948d24cc53311ad8e5de74ec16a7e07145b7c18c885094">FILTER_LINEAR</a></div><div class="ttdeci">@ FILTER_LINEAR</div><div class="ttdoc">Bilinear filtering.</div><div class="ttdef"><b>Definition:</b> cudaFilterMode.h:38</div></div>
<div class="ttc" id="agroup__depthNet_html_a9a9695fc22a0468a1688cfeaf806ce8b"><div class="ttname"><a href="group__depthNet.html#a9a9695fc22a0468a1688cfeaf806ce8b">depthNet::SavePointCloud</a></div><div class="ttdeci">bool SavePointCloud(const char *filename)</div><div class="ttdoc">Extract and save the point cloud to a PCD file (depth only).</div></div>
<div class="ttc" id="agroup__depthNet_html_a8f9f8636a7bf4c3bbf6da267b550a136"><div class="ttname"><a href="group__depthNet.html#a8f9f8636a7bf4c3bbf6da267b550a136">depthNet::mHistogramPDF</a></div><div class="ttdeci">float * mHistogramPDF</div><div class="ttdef"><b>Definition:</b> depthNet.h:269</div></div>
<div class="ttc" id="agroup__colormap_html_ggab66101108d92e39f9ab9283c31da3550a0d0fcdcd836507523dea555ce4a89632"><div class="ttname"><a href="group__colormap.html#ggab66101108d92e39f9ab9283c31da3550a0d0fcdcd836507523dea555ce4a89632">COLORMAP_VIRIDIS_INVERTED</a></div><div class="ttdeci">@ COLORMAP_VIRIDIS_INVERTED</div><div class="ttdoc">Viridis colormap (inverted), see http://bids.github.io/colormap/.</div><div class="ttdef"><b>Definition:</b> cudaColormap.h:52</div></div>
<div class="ttc" id="agroup__depthNet_html_a5080fdfd97015e8e77aba3e33275ac37"><div class="ttname"><a href="group__depthNet.html#a5080fdfd97015e8e77aba3e33275ac37">depthNet::GetDepthFieldHeight</a></div><div class="ttdeci">uint32_t GetDepthFieldHeight() const</div><div class="ttdoc">Return the height of the depth field.</div><div class="ttdef"><b>Definition:</b> depthNet.h:224</div></div>
<div class="ttc" id="agroup__depthNet_html_a5d882ef0255213a1950659b661f99424"><div class="ttname"><a href="group__depthNet.html#a5d882ef0255213a1950659b661f99424">depthNet::VisualizationFlagsFromStr</a></div><div class="ttdeci">static uint32_t VisualizationFlagsFromStr(const char *str, uint32_t default_value=VISUALIZE_INPUT|VISUALIZE_DEPTH)</div><div class="ttdoc">Parse a string of one of more VisualizationMode values.</div></div>
<div class="ttc" id="agroup__depthNet_html_a91a76621c0a3ce9d0b12acc52e6061a9"><div class="ttname"><a href="group__depthNet.html#a91a76621c0a3ce9d0b12acc52e6061a9">depthNet::mHistogramEDU</a></div><div class="ttdeci">uint32_t * mHistogramEDU</div><div class="ttdef"><b>Definition:</b> depthNet.h:271</div></div>
<div class="ttc" id="agroup__depthNet_html_a1928879f3bb2f489d93c0d122ce2dc4b"><div class="ttname"><a href="group__depthNet.html#a1928879f3bb2f489d93c0d122ce2dc4b">depthNet::mHistogramCDF</a></div><div class="ttdeci">float * mHistogramCDF</div><div class="ttdef"><b>Definition:</b> depthNet.h:270</div></div>
<div class="ttc" id="agroup__depthNet_html_afca2eec512a7d7945a9e404eb8e40a56"><div class="ttname"><a href="group__depthNet.html#afca2eec512a7d7945a9e404eb8e40a56">depthNet::Process</a></div><div class="ttdeci">bool Process(T *image, uint32_t width, uint32_t height)</div><div class="ttdoc">Compute the depth field from a monocular RGB/RGBA image.</div><div class="ttdef"><b>Definition:</b> depthNet.h:148</div></div>
<div class="ttc" id="agroup__tensorNet_html_ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b"><div class="ttname"><a href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a></div><div class="ttdeci">@ DEVICE_GPU</div><div class="ttdoc">GPU (if multiple GPUs are present, a specific GPU can be selected with cudaSetDevice()</div><div class="ttdef"><b>Definition:</b> tensorNet.h:131</div></div>
<div class="ttc" id="atensorNet_8h_html_a64c8f3dfeacfa962ff9e23c586aedd1b"><div class="ttname"><a href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">Dims3</a></div><div class="ttdeci">nvinfer1::Dims3 Dims3</div><div class="ttdef"><b>Definition:</b> tensorNet.h:58</div></div>
<div class="ttc" id="agroup__depthNet_html_a145bebabbf410e9e74e0d8a040015b1d"><div class="ttname"><a href="group__depthNet.html#a145bebabbf410e9e74e0d8a040015b1d">depthNet::allocHistogramBuffers</a></div><div class="ttdeci">bool allocHistogramBuffers()</div></div>
<div class="ttc" id="agroup__colormap_html_ggab66101108d92e39f9ab9283c31da3550a02b62792467077e77c5d4cdc8e9e1968"><div class="ttname"><a href="group__colormap.html#ggab66101108d92e39f9ab9283c31da3550a02b62792467077e77c5d4cdc8e9e1968">COLORMAP_DEFAULT</a></div><div class="ttdeci">@ COLORMAP_DEFAULT</div><div class="ttdef"><b>Definition:</b> cudaColormap.h:60</div></div>
<div class="ttc" id="agroup__depthNet_html_ae7d152624a7678216ac148e6d025e963"><div class="ttname"><a href="group__depthNet.html#ae7d152624a7678216ac148e6d025e963">depthNet::Visualize</a></div><div class="ttdeci">bool Visualize(T *output, uint32_t width, uint32_t height, cudaColormapType colormap=COLORMAP_DEFAULT, cudaFilterMode filter=FILTER_LINEAR)</div><div class="ttdoc">Visualize the raw depth field into a colorized RGB/RGBA depth map.</div><div class="ttdef"><b>Definition:</b> depthNet.h:199</div></div>
<div class="ttc" id="agroup__tensorNet_html_gaa5d3f9981cdbd91516c1474006a80fe4"><div class="ttname"><a href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a></div><div class="ttdeci">deviceType</div><div class="ttdoc">Enumeration for indicating the desired device that the network should run on, if available in hardwar...</div><div class="ttdef"><b>Definition:</b> tensorNet.h:129</div></div>
<div class="ttc" id="agroup__depthNet_html_a96554b8c9ba3e710de7fe45f9edc8fc7"><div class="ttname"><a href="group__depthNet.html#a96554b8c9ba3e710de7fe45f9edc8fc7">depthNet::GetDepthField</a></div><div class="ttdeci">float * GetDepthField() const</div><div class="ttdoc">Return the raw depth field.</div><div class="ttdef"><b>Definition:</b> depthNet.h:214</div></div>
<div class="ttc" id="agroup__depthNet_html_a79173edc788bdf267e4622ad0f52e476a8675b85af577753f73916d1087ff3c4e"><div class="ttname"><a href="group__depthNet.html#a79173edc788bdf267e4622ad0f52e476a8675b85af577753f73916d1087ff3c4e">depthNet::VISUALIZE_DEPTH</a></div><div class="ttdeci">@ VISUALIZE_DEPTH</div><div class="ttdoc">Display the colorized depth field.</div><div class="ttdef"><b>Definition:</b> depthNet.h:76</div></div>
<div class="ttc" id="agroup__depthNet_html_gab90d8bf9344740081e4c51c014e73c52"><div class="ttname"><a href="group__depthNet.html#gab90d8bf9344740081e4c51c014e73c52">DEPTHNET_DEFAULT_INPUT</a></div><div class="ttdeci">#define DEPTHNET_DEFAULT_INPUT</div><div class="ttdoc">Name of default input blob for depthNet model.</div><div class="ttdef"><b>Definition:</b> depthNet.h:34</div></div>
<div class="ttc" id="atensorNet_8h_html"><div class="ttname"><a href="tensorNet_8h.html">tensorNet.h</a></div></div>
<div class="ttc" id="atensorNet_8h_html_a1fc0b1785ea99bd75ec83b1eeb4e6120"><div class="ttname"><a href="tensorNet_8h.html#a1fc0b1785ea99bd75ec83b1eeb4e6120">DIMS_H</a></div><div class="ttdeci">#define DIMS_H(x)</div><div class="ttdef"><b>Definition:</b> tensorNet.h:61</div></div>
<div class="ttc" id="agroup__tensorNet_html_ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9"><div class="ttname"><a href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a></div><div class="ttdeci">@ TYPE_FASTEST</div><div class="ttdoc">The fastest detected precision should be use (i.e.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:105</div></div>
<div class="ttc" id="agroup__depthNet_html_aae07945d10ca9881850400600cf10d08"><div class="ttname"><a href="group__depthNet.html#aae07945d10ca9881850400600cf10d08">depthNet::Process</a></div><div class="ttdeci">bool Process(T1 *input, uint32_t input_width, uint32_t input_height, T2 *output, uint32_t output_width, uint32_t output_height, cudaColormapType colormap=COLORMAP_DEFAULT, cudaFilterMode filter=FILTER_LINEAR)</div><div class="ttdoc">Process an RGB/RGBA image and map the depth image with the specified colormap.</div><div class="ttdef"><b>Definition:</b> depthNet.h:180</div></div>
<div class="ttc" id="agroup__depthNet_html_a7b7805b7e1875bd7138e19a9949f1318"><div class="ttname"><a href="group__depthNet.html#a7b7805b7e1875bd7138e19a9949f1318">depthNet::depthNet</a></div><div class="ttdeci">depthNet()</div></div>
<div class="ttc" id="agroup__cudaFilter_html_ga25d4283643163befe99948d24cc53311"><div class="ttname"><a href="group__cudaFilter.html#ga25d4283643163befe99948d24cc53311">cudaFilterMode</a></div><div class="ttdeci">cudaFilterMode</div><div class="ttdoc">Enumeration of interpolation filtering modes.</div><div class="ttdef"><b>Definition:</b> cudaFilterMode.h:35</div></div>
<div class="ttc" id="agroup__depthNet_html_a79173edc788bdf267e4622ad0f52e476a8e00a42ee2103dc6081b8886553b9c91"><div class="ttname"><a href="group__depthNet.html#a79173edc788bdf267e4622ad0f52e476a8e00a42ee2103dc6081b8886553b9c91">depthNet::VISUALIZE_INPUT</a></div><div class="ttdeci">@ VISUALIZE_INPUT</div><div class="ttdoc">Display the original input image.</div><div class="ttdef"><b>Definition:</b> depthNet.h:75</div></div>
<div class="ttc" id="agroup__depthNet_html_ada432dd3799aaaa621330be631330165"><div class="ttname"><a href="group__depthNet.html#ada432dd3799aaaa621330be631330165">depthNet::Create</a></div><div class="ttdeci">static depthNet * Create(const char *network=&quot;fcn-mobilenet&quot;, uint32_t maxBatchSize=DEFAULT_MAX_BATCH_SIZE, precisionType precision=TYPE_FASTEST, deviceType device=DEVICE_GPU, bool allowGPUFallback=true)</div><div class="ttdoc">Load a pre-trained model.</div></div>
<div class="ttc" id="agroup__depthNet_html_ade3376a680252cf2aa68f0f1945a6b71"><div class="ttname"><a href="group__depthNet.html#ade3376a680252cf2aa68f0f1945a6b71">depthNet::Usage</a></div><div class="ttdeci">static const char * Usage()</div><div class="ttdoc">Usage string for command line arguments to Create()</div><div class="ttdef"><b>Definition:</b> depthNet.h:137</div></div>
<div class="ttc" id="agroup__tensorNet_html_gaac6604fd52c6e5db82877390e0378623"><div class="ttname"><a href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a></div><div class="ttdeci">precisionType</div><div class="ttdoc">Enumeration for indicating the desired precision that the network should run in, if available in hard...</div><div class="ttdef"><b>Definition:</b> tensorNet.h:102</div></div>
<div class="ttc" id="agroup__depthNet_html_classdepthNet"><div class="ttname"><a href="group__depthNet.html#classdepthNet">depthNet</a></div><div class="ttdoc">Mono depth estimation from monocular images, using TensorRT.</div><div class="ttdef"><b>Definition:</b> depthNet.h:67</div></div>
<div class="ttc" id="agroup__tensorNet_html_classtensorNet"><div class="ttname"><a href="group__tensorNet.html#classtensorNet">tensorNet</a></div><div class="ttdoc">Abstract class for loading a tensor network with TensorRT.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:218</div></div>
<div class="ttc" id="acudaColormap_8h_html"><div class="ttname"><a href="cudaColormap_8h.html">cudaColormap.h</a></div></div>
<div class="ttc" id="atensorNet_8h_html_a7d959cb65990da8bfea3d941d6daf416"><div class="ttname"><a href="tensorNet_8h.html#a7d959cb65990da8bfea3d941d6daf416">DIMS_W</a></div><div class="ttdeci">#define DIMS_W(x)</div><div class="ttdef"><b>Definition:</b> tensorNet.h:62</div></div>
<div class="ttc" id="agroup__depthNet_html_a25ba6711b1c348cf92f0e8c06b703719"><div class="ttname"><a href="group__depthNet.html#a25ba6711b1c348cf92f0e8c06b703719">depthNet::mDepthRange</a></div><div class="ttdeci">int2 * mDepthRange</div><div class="ttdef"><b>Definition:</b> depthNet.h:266</div></div>
<div class="ttc" id="agroup__colormap_html_gab66101108d92e39f9ab9283c31da3550"><div class="ttname"><a href="group__colormap.html#gab66101108d92e39f9ab9283c31da3550">cudaColormapType</a></div><div class="ttdeci">cudaColormapType</div><div class="ttdoc">Enumeration of built-in colormaps.</div><div class="ttdef"><b>Definition:</b> cudaColormap.h:36</div></div>
<div class="ttc" id="agroup__tensorNet_html_ga5a46a965749d6118e01307fd4d4865c9"><div class="ttname"><a href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a></div><div class="ttdeci">#define DEFAULT_MAX_BATCH_SIZE</div><div class="ttdoc">Default maximum batch size.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:88</div></div>
<div class="ttc" id="agroup__commandLine_html_classcommandLine"><div class="ttname"><a href="group__commandLine.html#classcommandLine">commandLine</a></div><div class="ttdoc">Command line parser for extracting flags, values, and strings.</div><div class="ttdef"><b>Definition:</b> commandLine.h:35</div></div>
<div class="ttc" id="agroup__depthNet_html_a397efef0c43950e8aa2048bf4cf1b1b8"><div class="ttname"><a href="group__depthNet.html#a397efef0c43950e8aa2048bf4cf1b1b8">depthNet::mHistogram</a></div><div class="ttdeci">uint32_t * mHistogram</div><div class="ttdef"><b>Definition:</b> depthNet.h:268</div></div>
<div class="ttc" id="agroup__depthNet_html_a8fb7e1b625a0b9f6d4e046863aceb6ec"><div class="ttname"><a href="group__depthNet.html#a8fb7e1b625a0b9f6d4e046863aceb6ec">depthNet::histogramEqualizationCUDA</a></div><div class="ttdeci">bool histogramEqualizationCUDA()</div></div>
<div class="ttc" id="agroup__imageFormat_html_ga931c48e08f361637d093355d64583406"><div class="ttname"><a href="group__imageFormat.html#ga931c48e08f361637d093355d64583406">imageFormat</a></div><div class="ttdeci">imageFormat</div><div class="ttdoc">The imageFormat enum is used to identify the pixel format and colorspace of an image.</div><div class="ttdef"><b>Definition:</b> imageFormat.h:49</div></div>
<div class="ttc" id="agroup__depthNet_html_a79173edc788bdf267e4622ad0f52e476"><div class="ttname"><a href="group__depthNet.html#a79173edc788bdf267e4622ad0f52e476">depthNet::VisualizationFlags</a></div><div class="ttdeci">VisualizationFlags</div><div class="ttdoc">Visualization flags.</div><div class="ttdef"><b>Definition:</b> depthNet.h:73</div></div>
<div class="ttc" id="agroup__tensorNet_html_afcdbdb26dc6e5117f867c83e635a0250"><div class="ttname"><a href="group__tensorNet.html#afcdbdb26dc6e5117f867c83e635a0250">tensorNet::mOutputs</a></div><div class="ttdeci">std::vector&lt; layerInfo &gt; mOutputs</div><div class="ttdef"><b>Definition:</b> tensorNet.h:819</div></div>
<div class="ttc" id="agroup__depthNet_html_a67957d14b680b3d2ef001a55727e3f1d"><div class="ttname"><a href="group__depthNet.html#a67957d14b680b3d2ef001a55727e3f1d">depthNet::GetDepthFieldWidth</a></div><div class="ttdeci">uint32_t GetDepthFieldWidth() const</div><div class="ttdoc">Return the width of the depth field.</div><div class="ttdef"><b>Definition:</b> depthNet.h:219</div></div>
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